dv = "score.CI"
dv.pos = "score.CI.pos"
dv.pre = "score.CI.pre"

fatores2 <- c("genero","zona.participante","zona.escola","score.CI.quintile")
lfatores2 <- as.list(fatores2)
names(lfatores2) <- fatores2

fatores1 <- c("grupo", fatores2)
lfatores1 <- as.list(fatores1)
names(lfatores1) <- fatores1

lfatores <- c(lfatores1)

color <- list()
color[["prepost"]] = c("#ffee65","#f28e2B")
color[["grupo"]] = c("#bcbd22","#fd7f6f")
color[["genero"]] = c("#FF007F","#4D4DFF")
color[["zona.escola"]] = c("#AA00FF","#00CCCC")
color[["zona.participante"]] = c("#AA00FF","#00CCCC")

level <- list()
level[["grupo"]] = c("Controle","Experimental")
level[["genero"]] = c("F","M")
level[["zona.escola"]] = c("Rural","Urbana")
level[["zona.participante"]] = c("Rural","Urbana")

# ..

ymin <- 0
ymax <- 0

ymin.ci <- 0
ymax.ci <- 0


color[["grupo:genero"]] = c(
  "Controle:F"="#ff99cb", "Controle:M"="#b7b7ff",
  "Experimental:F"="#FF007F", "Experimental:M"="#4D4DFF",
  "Controle.F"="#ff99cb", "Controle.M"="#b7b7ff",
  "Experimental.F"="#FF007F", "Experimental.M"="#4D4DFF"
)
color[["grupo:zona.escola"]] = c(
  "Controle:Rural"="#b2efef","Controle:Urbana"="#e5b2ff",
  "Experimental:Rural"="#00CCCC", "Experimental:Urbana"="#AA00FF",
  "Controle.Rural"="#b2efef","Controle.Urbana"="#e5b2ff",
  "Experimental.Rural"="#00CCCC", "Experimental.Urbana"="#AA00FF"
)
color[["grupo:zona.participante"]] = c(
  "Controle:Rural"="#b2efef","Controle:Urbana"="#e5b2ff",
  "Experimental:Rural"="#00CCCC", "Experimental:Urbana"="#AA00FF",
  "Controle.Rural"="#b2efef","Controle.Urbana"="#e5b2ff",
  "Experimental.Rural"="#00CCCC", "Experimental.Urbana"="#AA00FF"
)

for (coln in c(
  "palavras.lidas","score.compreensao","tri.compreensao",
  "score.vocab","tri.vocab",
  "score.vocab.ensinado","tri.vocab.ensinado","score.vocab.nao.ensinado","tri.vocab.nao.ensinado",
  "score.CLPP","tri.CLPP","score.CR","tri.CR",
  "score.CI","tri.CI","score.TV","tri.TV","score.TF","tri.TF","score.TO","tri.TO")) {
  color[[paste0(coln,".quintile")]] = c("#BF0040","#FF0000","#800080","#0000FF","#4000BF")
  level[[paste0(coln,".quintile")]] = c("1st quintile","2nd quintile","3rd quintile","4th quintile","5th quintile")
  color[[paste0("grupo:",coln,".quintile")]] = c(
    "Experimental.1st quintile"="#BF0040", "Controle.1st quintile"="#d8668c",
    "Experimental.2nd quintile"="#FF0000", "Controle.2nd quintile"="#ff7f7f",
    "Experimental.3rd quintile"="#8fce00", "Controle.3rd quintile"="#ddf0b2",
    "Experimental.4th quintile"="#0000FF", "Controle.4th quintile"="#b2b2ff",
    "Experimental.5th quintile"="#4000BF", "Controle.5th quintile"="#b299e5",
    
    "Experimental:1st quintile"="#BF0040", "Controle:1st quintile"="#d8668c",
    "Experimental:2nd quintile"="#FF0000", "Controle:2nd quintile"="#ff7f7f",
    "Experimental:3rd quintile"="#8fce00", "Controle:3rd quintile"="#ddf0b2",
    "Experimental:4th quintile"="#0000FF", "Controle:4th quintile"="#b2b2ff",
    "Experimental:5th quintile"="#4000BF", "Controle:5th quintile"="#b299e5")
}


gdat <- read_excel("../data/data.xlsx", sheet = "leitura.st")



dat <- gdat
dat$grupo <- factor(dat[["grupo"]], level[["grupo"]])
for (coln in c(names(lfatores))) {
  dat[[coln]] <- factor(dat[[coln]], level[[coln]][level[[coln]] %in% unique(dat[[coln]])])
}
dat <- dat[which(!is.na(dat[[dv.pre]]) & !is.na(dat[[dv.pos]])),]
dat <- dat[,c("id",names(lfatores),dv.pre,dv.pos)]

dat.long <- rbind(dat, dat)
dat.long$time <- c(rep("pre", nrow(dat)), rep("pos", nrow(dat)))
dat.long$time <- factor(dat.long$time, c("pre","pos"))
dat.long[[dv]] <- c(dat[[dv.pre]], dat[[dv.pos]])


for (f in c("grupo", names(lfatores))) {
  if (is.null(color[[f]]) && length(unique(dat[[f]])) > 0) 
      color[[f]] <- distinctColorPalette(length(unique(dat[[f]])))
}
for (f in c(fatores2)) {
  if (is.null(color[[paste0("grupo:",f)]]) && length(unique(dat[[f]])) > 0)
    color[[paste0("grupo:",f)]] <- distinctColorPalette(length(unique(dat[["grupo"]]))*length(unique(dat[[f]])))
}

ldat <- list()
laov <- list()
lpwc <- list()
lemms <- list()

df <- get.descriptives(dat, c(dv.pre, dv.pos), c("grupo"), 
                       include.global = T, symmetry.test = T, normality.test = F)
df <- plyr::rbind.fill(
  df, do.call(plyr::rbind.fill, lapply(lfatores2, FUN = function(f) {
    if (nrow(dat) > 0 && sum(!is.na(unique(dat[[f]]))) > 1)
      get.descriptives(dat, c(dv.pre,dv.pos), c("grupo", f),
                       symmetry.test = T, normality.test = F)
    }))
)
df <- df[,c(fatores1[fatores1 %in% colnames(df)],"variable",
            colnames(df)[!colnames(df) %in% c(fatores1,"variable")])]

pdat = remove_group_data(dat[!is.na(dat[["grupo"]]),], "score.CI.pos", "grupo")

pdat.long <- rbind(pdat[,c("id","grupo")], pdat[,c("id","grupo")])
pdat.long[["time"]] <- c(rep("pre", nrow(pdat)), rep("pos", nrow(pdat)))
pdat.long[["time"]] <- factor(pdat.long[["time"]], c("pre","pos"))
pdat.long[["score.CI"]] <- c(pdat[["score.CI.pre"]], pdat[["score.CI.pos"]])

aov = anova_test(pdat, score.CI.pos ~ score.CI.pre + grupo)
laov[["grupo"]] <- get_anova_table(aov)

pwc <- emmeans_test(pdat, score.CI.pos ~ grupo, covariate = score.CI.pre,
                    p.adjust.method = "bonferroni")

pwc.long <- emmeans_test(dplyr::group_by_at(pdat.long, "grupo"),
                          score.CI ~ time,
                          p.adjust.method = "bonferroni")
lpwc[["grupo"]] <- plyr::rbind.fill(pwc, pwc.long)

ds <- get.descriptives(pdat, "score.CI.pos", "grupo", covar = "score.CI.pre")
ds <- merge(ds[ds$variable != "score.CI.pre",],
            ds[ds$variable == "score.CI.pre", !colnames(ds) %in% c("variable")],
            by = "grupo", all.x = T, suffixes = c("", ".score.CI.pre"))
ds <- merge(get_emmeans(pwc), ds, by = "grupo", suffixes = c(".emms", ""))
ds <- ds[,c("grupo","n","mean.score.CI.pre","se.score.CI.pre","mean","se",
            "emmean","se.emms","conf.low","conf.high")]

colnames(ds) <- c("grupo", "N", paste0(c("M","SE")," (pre)"),
                  paste0(c("M","SE"), " (unadj)"),
                  paste0(c("M", "SE"), " (adj)"), "conf.low", "conf.high")

lemms[["grupo"]] <- ds

wdat = pdat 

res = residuals(lm(score.CI.pos ~ score.CI.pre + grupo, data = wdat))
non.normal = getNonNormal(res, wdat$id, plimit = 0.05)

wdat = wdat[!wdat$id %in% non.normal,]

wdat.long <- rbind(wdat[,c("id","grupo")], wdat[,c("id","grupo")])
wdat.long[["time"]] <- c(rep("pre", nrow(wdat)), rep("pos", nrow(wdat)))
wdat.long[["time"]] <- factor(wdat.long[["time"]], c("pre","pos"))
wdat.long[["score.CI"]] <- c(wdat[["score.CI.pre"]], wdat[["score.CI.pos"]])

ldat[["grupo"]] = wdat

(non.normal)

aov = anova_test(wdat, score.CI.pos ~ score.CI.pre + grupo)
laov[["grupo"]] <- merge(get_anova_table(aov), laov[["grupo"]],
                            by="Effect", suffixes = c("","'"))

(df = get_anova_table(aov))

pwc <- emmeans_test(wdat, score.CI.pos ~ grupo, covariate = score.CI.pre,
                    p.adjust.method = "bonferroni")

pwc.long <- emmeans_test(dplyr::group_by_at(wdat.long, "grupo"),
                         score.CI ~ time,
                         p.adjust.method = "bonferroni")
lpwc[["grupo"]] <- merge(plyr::rbind.fill(pwc, pwc.long), lpwc[["grupo"]],
                            by=c("grupo","term",".y.","group1","group2"),
                            suffixes = c("","'"))

ds <- get.descriptives(wdat, "score.CI.pos", "grupo", covar = "score.CI.pre")
ds <- merge(ds[ds$variable != "score.CI.pre",],
            ds[ds$variable == "score.CI.pre", !colnames(ds) %in% c("variable")],
            by = "grupo", all.x = T, suffixes = c("", ".score.CI.pre"))
ds <- merge(get_emmeans(pwc), ds, by = "grupo", suffixes = c(".emms", ""))
ds <- ds[,c("grupo","n","mean.score.CI.pre","se.score.CI.pre","mean","se",
            "emmean","se.emms","conf.low","conf.high")]

colnames(ds) <- c("grupo", "N", paste0(c("M","SE")," (pre)"),
                  paste0(c("M","SE"), " (unadj)"),
                  paste0(c("M", "SE"), " (adj)"), "conf.low", "conf.high")

lemms[["grupo"]] <- merge(ds, lemms[["grupo"]], by=c("grupo"), suffixes = c("","'"))

plots <- oneWayAncovaPlots(
  wdat, "score.CI.pos", "grupo", aov, list("grupo"=pwc), addParam = c("mean_ci"),
  font.label.size=10, step.increase=0.05, p.label="p.adj",
  subtitle = which(aov$Effect == "grupo"))

if (!is.null(nrow(plots[["grupo"]]$data)))
  plots[["grupo"]] + ggplot2::ylab("Reading Irregular Correct Words") + 
  if (ymin.ci < ymax.ci) ggplot2::ylim(ymin.ci, ymax.ci)

plots <- oneWayAncovaBoxPlots(
  wdat, "score.CI.pos", "grupo", aov, pwc, covar = "score.CI.pre",
  theme = "classic", color = color[["grupo"]],
  subtitle = which(aov$Effect == "grupo"))

if (length(unique(wdat[["grupo"]])) > 1)
  plots[["grupo"]] + ggplot2::ylab("Reading Irregular Correct Words") +
  ggplot2::scale_x_discrete(labels=c('pre', 'pos')) +
  if (ymin < ymax) ggplot2::ylim(ymin, ymax)

if (length(unique(wdat.long[["grupo"]])) > 1)
  plots <- oneWayAncovaBoxPlots(
    wdat.long, "score.CI", "grupo", aov, pwc.long,
    pre.post = "time", theme = "classic", color = color$prepost)

if (length(unique(wdat.long[["grupo"]])) > 1)
  plots[["grupo"]] + ggplot2::ylab("Reading Irregular Correct Words") +
  if (ymin < ymax) ggplot2::ylim(ymin, ymax) 

ggscatter(wdat, x = "score.CI.pre", y = "score.CI.pos", size = 0.5,
          color = "grupo", add = "reg.line")+
  stat_regline_equation(
    aes(label =  paste(..eq.label.., ..rr.label.., sep = "~~~~"), color = grupo)
  ) +
  ggplot2::labs(subtitle = rstatix::get_test_label(aov, detailed = T, row = which(aov$Effect == "grupo"))) +
  ggplot2::scale_color_manual(values = color[["grupo"]]) +
  ggplot2::ylab("Reading Irregular Correct Words")  +
  if (ymin < ymax) ggplot2::ylim(ymin, ymax)

res <- augment(lm(score.CI.pos ~ score.CI.pre + grupo, data = wdat))

shapiro_test(res$.resid)

levene_test(res, .resid ~ grupo)

pdat = remove_group_data(dat[!is.na(dat[["grupo"]]) & !is.na(dat[["genero"]]),],
                         "score.CI.pos", c("grupo","genero"))
pdat = pdat[pdat[["genero"]] %in% do.call(
  intersect, lapply(unique(pdat[["grupo"]]), FUN = function(x) {
    unique(pdat[["genero"]][which(pdat[["grupo"]] == x)])
  })),]
pdat[["grupo"]] = factor(pdat[["grupo"]], level[["grupo"]])
pdat[["genero"]] = factor(
  pdat[["genero"]],
  level[["genero"]][level[["genero"]] %in% unique(pdat[["genero"]])])

pdat.long <- rbind(pdat[,c("id","grupo","genero")], pdat[,c("id","grupo","genero")])
pdat.long[["time"]] <- c(rep("pre", nrow(pdat)), rep("pos", nrow(pdat)))
pdat.long[["time"]] <- factor(pdat.long[["time"]], c("pre","pos"))
pdat.long[["score.CI"]] <- c(pdat[["score.CI.pre"]], pdat[["score.CI.pos"]])

if (length(unique(pdat[["genero"]])) >= 2) {
  aov = anova_test(pdat, score.CI.pos ~ score.CI.pre + grupo*genero)
  laov[["grupo:genero"]] <- get_anova_table(aov)
}

if (length(unique(pdat[["genero"]])) >= 2) {
  pwcs <- list()
  pwcs[["genero"]] <- emmeans_test(
    group_by(pdat, grupo), score.CI.pos ~ genero,
    covariate = score.CI.pre, p.adjust.method = "bonferroni")
  pwcs[["grupo"]] <- emmeans_test(
    group_by(pdat, genero), score.CI.pos ~ grupo,
    covariate = score.CI.pre, p.adjust.method = "bonferroni")
  
  pwc <- plyr::rbind.fill(pwcs[["grupo"]], pwcs[["genero"]])
  pwc <- pwc[,c("grupo","genero", colnames(pwc)[!colnames(pwc) %in% c("grupo","genero")])]
}

if (length(unique(pdat[["genero"]])) >= 2) {
  pwc.long <- emmeans_test(dplyr::group_by_at(pdat.long, c("grupo","genero")),
                           score.CI ~ time,
                           p.adjust.method = "bonferroni")
  lpwc[["grupo:genero"]] <- plyr::rbind.fill(pwc, pwc.long)
}

if (length(unique(pdat[["genero"]])) >= 2) {
  ds <- get.descriptives(pdat, "score.CI.pos", c("grupo","genero"), covar = "score.CI.pre")
  ds <- merge(ds[ds$variable != "score.CI.pre",],
              ds[ds$variable == "score.CI.pre", !colnames(ds) %in% c("variable")],
              by = c("grupo","genero"), all.x = T, suffixes = c("", ".score.CI.pre"))
  ds <- merge(get_emmeans(pwcs[["grupo"]]), ds,
              by = c("grupo","genero"), suffixes = c(".emms", ""))
  ds <- ds[,c("grupo","genero","n","mean.score.CI.pre","se.score.CI.pre","mean","se",
              "emmean","se.emms","conf.low","conf.high")]
  
  colnames(ds) <- c("grupo","genero", "N", paste0(c("M","SE")," (pre)"),
                    paste0(c("M","SE"), " (unadj)"),
                    paste0(c("M", "SE"), " (adj)"), "conf.low", "conf.high")
  
  lemms[["grupo:genero"]] <- ds
}

if (length(unique(pdat[["genero"]])) >= 2) {
  wdat = pdat 
  
  res = residuals(lm(score.CI.pos ~ score.CI.pre + grupo*genero, data = wdat))
  non.normal = getNonNormal(res, wdat$id, plimit = 0.05)
  
  wdat = wdat[!wdat$id %in% non.normal,]
  
  wdat.long <- rbind(wdat[,c("id","grupo","genero")], wdat[,c("id","grupo","genero")])
  wdat.long[["time"]] <- c(rep("pre", nrow(wdat)), rep("pos", nrow(wdat)))
  wdat.long[["time"]] <- factor(wdat.long[["time"]], c("pre","pos"))
  wdat.long[["score.CI"]] <- c(wdat[["score.CI.pre"]], wdat[["score.CI.pos"]])
  
  
  ldat[["grupo:genero"]] = wdat
  
  (non.normal)
}

if (length(unique(pdat[["genero"]])) >= 2) {
  aov = anova_test(wdat, score.CI.pos ~ score.CI.pre + grupo*genero)
  laov[["grupo:genero"]] <- merge(get_anova_table(aov), laov[["grupo:genero"]],
                                         by="Effect", suffixes = c("","'"))
  df = get_anova_table(aov)
}

if (length(unique(pdat[["genero"]])) >= 2) {
  pwcs <- list()
  pwcs[["genero"]] <- emmeans_test(
    group_by(wdat, grupo), score.CI.pos ~ genero,
    covariate = score.CI.pre, p.adjust.method = "bonferroni")
  pwcs[["grupo"]] <- emmeans_test(
    group_by(wdat, genero), score.CI.pos ~ grupo,
    covariate = score.CI.pre, p.adjust.method = "bonferroni")
  
  pwc <- plyr::rbind.fill(pwcs[["grupo"]], pwcs[["genero"]])
  pwc <- pwc[,c("grupo","genero", colnames(pwc)[!colnames(pwc) %in% c("grupo","genero")])]
}

if (length(unique(pdat[["genero"]])) >= 2) {
  pwc.long <- emmeans_test(dplyr::group_by_at(wdat.long, c("grupo","genero")),
                           score.CI ~ time,
                           p.adjust.method = "bonferroni")
  lpwc[["grupo:genero"]] <- merge(plyr::rbind.fill(pwc, pwc.long),
                                         lpwc[["grupo:genero"]],
                                         by=c("grupo","genero","term",".y.","group1","group2"),
                                         suffixes = c("","'"))
}

if (length(unique(pdat[["genero"]])) >= 2) {
  ds <- get.descriptives(wdat, "score.CI.pos", c("grupo","genero"), covar = "score.CI.pre")
  ds <- merge(ds[ds$variable != "score.CI.pre",],
              ds[ds$variable == "score.CI.pre", !colnames(ds) %in% c("variable")],
              by = c("grupo","genero"), all.x = T, suffixes = c("", ".score.CI.pre"))
  ds <- merge(get_emmeans(pwcs[["grupo"]]), ds,
              by = c("grupo","genero"), suffixes = c(".emms", ""))
  ds <- ds[,c("grupo","genero","n","mean.score.CI.pre","se.score.CI.pre",
              "mean","se","emmean","se.emms","conf.low","conf.high")]
  
  colnames(ds) <- c("grupo","genero", "N", paste0(c("M","SE")," (pre)"),
                    paste0(c("M","SE"), " (unadj)"),
                    paste0(c("M", "SE"), " (adj)"), "conf.low", "conf.high")
  
  lemms[["grupo:genero"]] <- merge(ds, lemms[["grupo:genero"]],
                                          by=c("grupo","genero"), suffixes = c("","'"))
}

if (length(unique(pdat[["genero"]])) >= 2) {
  ggPlotAoC2(pwcs, "grupo", "genero", aov, ylab = "Reading Irregular Correct Words",
             subtitle = which(aov$Effect == "grupo:genero"), addParam = "errorbar") +
    ggplot2::scale_color_manual(values = color[["genero"]]) +
    ggplot2::ylab("Reading Irregular Correct Words") +
    if (ymin.ci < ymax.ci) ggplot2::ylim(ymin.ci, ymax.ci)
}

if (length(unique(pdat[["genero"]])) >= 2) {
  ggPlotAoC2(pwcs, "genero", "grupo", aov, ylab = "Reading Irregular Correct Words",
               subtitle = which(aov$Effect == "grupo:genero"), addParam = "errorbar") +
    ggplot2::scale_color_manual(values = color[["grupo"]]) +
    ggplot2::ylab("Reading Irregular Correct Words") +
    if (ymin.ci < ymax.ci) ggplot2::ylim(ymin.ci, ymax.ci)
}

if (length(unique(pdat[["genero"]])) >= 2) {
  plots <- twoWayAncovaBoxPlots(
    wdat, "score.CI.pos", c("grupo","genero"), aov, pwcs, covar = "score.CI.pre",
    theme = "classic", color = color[["grupo:genero"]],
    subtitle = which(aov$Effect == "grupo:genero"))
}

if (length(unique(pdat[["genero"]])) >= 2) {
  plots[["grupo:genero"]] + ggplot2::ylab("Reading Irregular Correct Words") +
  ggplot2::scale_x_discrete(labels=c('pre', 'pos')) +
  if (ymin < ymax) ggplot2::ylim(ymin, ymax)
}

if (length(unique(pdat[["genero"]])) >= 2) {
  plots <- twoWayAncovaBoxPlots(
    wdat.long, "score.CI", c("grupo","genero"), aov, pwc.long,
    pre.post = "time",
    theme = "classic", color = color$prepost)
}

if (length(unique(pdat[["genero"]])) >= 2) 
  plots[["grupo:genero"]] + ggplot2::ylab("Reading Irregular Correct Words") +
    if (ymin < ymax) ggplot2::ylim(ymin, ymax)

if (length(unique(pdat[["genero"]])) >= 2) {
  ggscatter(wdat, x = "score.CI.pre", y = "score.CI.pos", size = 0.5,
            facet.by = c("grupo","genero"), add = "reg.line")+
    stat_regline_equation(
      aes(label =  paste(..eq.label.., ..rr.label.., sep = "~~~~"))
    ) + ggplot2::ylab("Reading Irregular Correct Words") +
    if (ymin < ymax) ggplot2::ylim(ymin, ymax)
}

if (length(unique(pdat[["genero"]])) >= 2) {
  ggscatter(wdat, x = "score.CI.pre", y = "score.CI.pos", size = 0.5,
            color = "grupo", facet.by = "genero", add = "reg.line")+
    stat_regline_equation(
      aes(label =  paste(..eq.label.., ..rr.label.., sep = "~~~~"), color = grupo)
    ) +
    ggplot2::labs(subtitle = rstatix::get_test_label(aov, detailed = T, row = which(aov$Effect == "grupo:genero"))) +
    ggplot2::scale_color_manual(values = color[["grupo"]]) +
    ggplot2::ylab("Reading Irregular Correct Words") +
    if (ymin < ymax) ggplot2::ylim(ymin, ymax)
}

if (length(unique(pdat[["genero"]])) >= 2) {
  ggscatter(wdat, x = "score.CI.pre", y = "score.CI.pos", size = 0.5,
            color = "genero", facet.by = "grupo", add = "reg.line")+
    stat_regline_equation(
      aes(label =  paste(..eq.label.., ..rr.label.., sep = "~~~~"), color = genero)
    ) +
    ggplot2::labs(subtitle = rstatix::get_test_label(aov, detailed = T, row = which(aov$Effect == "grupo:genero"))) +
    ggplot2::scale_color_manual(values = color[["genero"]]) +
    ggplot2::ylab("Reading Irregular Correct Words") +
    if (ymin < ymax) ggplot2::ylim(ymin, ymax)
}

if (length(unique(pdat[["genero"]])) >= 2) 
  res <- augment(lm(score.CI.pos ~ score.CI.pre + grupo*genero, data = wdat))

if (length(unique(pdat[["genero"]])) >= 2)
  shapiro_test(res$.resid)

if (length(unique(pdat[["genero"]])) >= 2) 
  levene_test(res, .resid ~ grupo*genero)

pdat = remove_group_data(dat[!is.na(dat[["grupo"]]) & !is.na(dat[["zona.participante"]]),],
                         "score.CI.pos", c("grupo","zona.participante"))
pdat = pdat[pdat[["zona.participante"]] %in% do.call(
  intersect, lapply(unique(pdat[["grupo"]]), FUN = function(x) {
    unique(pdat[["zona.participante"]][which(pdat[["grupo"]] == x)])
  })),]
pdat[["grupo"]] = factor(pdat[["grupo"]], level[["grupo"]])
pdat[["zona.participante"]] = factor(
  pdat[["zona.participante"]],
  level[["zona.participante"]][level[["zona.participante"]] %in% unique(pdat[["zona.participante"]])])

pdat.long <- rbind(pdat[,c("id","grupo","zona.participante")], pdat[,c("id","grupo","zona.participante")])
pdat.long[["time"]] <- c(rep("pre", nrow(pdat)), rep("pos", nrow(pdat)))
pdat.long[["time"]] <- factor(pdat.long[["time"]], c("pre","pos"))
pdat.long[["score.CI"]] <- c(pdat[["score.CI.pre"]], pdat[["score.CI.pos"]])

if (length(unique(pdat[["zona.participante"]])) >= 2) {
  aov = anova_test(pdat, score.CI.pos ~ score.CI.pre + grupo*zona.participante)
  laov[["grupo:zona.participante"]] <- get_anova_table(aov)
}

if (length(unique(pdat[["zona.participante"]])) >= 2) {
  pwcs <- list()
  pwcs[["zona.participante"]] <- emmeans_test(
    group_by(pdat, grupo), score.CI.pos ~ zona.participante,
    covariate = score.CI.pre, p.adjust.method = "bonferroni")
  pwcs[["grupo"]] <- emmeans_test(
    group_by(pdat, zona.participante), score.CI.pos ~ grupo,
    covariate = score.CI.pre, p.adjust.method = "bonferroni")
  
  pwc <- plyr::rbind.fill(pwcs[["grupo"]], pwcs[["zona.participante"]])
  pwc <- pwc[,c("grupo","zona.participante", colnames(pwc)[!colnames(pwc) %in% c("grupo","zona.participante")])]
}

if (length(unique(pdat[["zona.participante"]])) >= 2) {
  pwc.long <- emmeans_test(dplyr::group_by_at(pdat.long, c("grupo","zona.participante")),
                           score.CI ~ time,
                           p.adjust.method = "bonferroni")
  lpwc[["grupo:zona.participante"]] <- plyr::rbind.fill(pwc, pwc.long)
}

if (length(unique(pdat[["zona.participante"]])) >= 2) {
  ds <- get.descriptives(pdat, "score.CI.pos", c("grupo","zona.participante"), covar = "score.CI.pre")
  ds <- merge(ds[ds$variable != "score.CI.pre",],
              ds[ds$variable == "score.CI.pre", !colnames(ds) %in% c("variable")],
              by = c("grupo","zona.participante"), all.x = T, suffixes = c("", ".score.CI.pre"))
  ds <- merge(get_emmeans(pwcs[["grupo"]]), ds,
              by = c("grupo","zona.participante"), suffixes = c(".emms", ""))
  ds <- ds[,c("grupo","zona.participante","n","mean.score.CI.pre","se.score.CI.pre","mean","se",
              "emmean","se.emms","conf.low","conf.high")]
  
  colnames(ds) <- c("grupo","zona.participante", "N", paste0(c("M","SE")," (pre)"),
                    paste0(c("M","SE"), " (unadj)"),
                    paste0(c("M", "SE"), " (adj)"), "conf.low", "conf.high")
  
  lemms[["grupo:zona.participante"]] <- ds
}

if (length(unique(pdat[["zona.participante"]])) >= 2) {
  wdat = pdat 
  
  res = residuals(lm(score.CI.pos ~ score.CI.pre + grupo*zona.participante, data = wdat))
  non.normal = getNonNormal(res, wdat$id, plimit = 0.05)
  
  wdat = wdat[!wdat$id %in% non.normal,]
  
  wdat.long <- rbind(wdat[,c("id","grupo","zona.participante")], wdat[,c("id","grupo","zona.participante")])
  wdat.long[["time"]] <- c(rep("pre", nrow(wdat)), rep("pos", nrow(wdat)))
  wdat.long[["time"]] <- factor(wdat.long[["time"]], c("pre","pos"))
  wdat.long[["score.CI"]] <- c(wdat[["score.CI.pre"]], wdat[["score.CI.pos"]])
  
  
  ldat[["grupo:zona.participante"]] = wdat
  
  (non.normal)
}

if (length(unique(pdat[["zona.participante"]])) >= 2) {
  aov = anova_test(wdat, score.CI.pos ~ score.CI.pre + grupo*zona.participante)
  laov[["grupo:zona.participante"]] <- merge(get_anova_table(aov), laov[["grupo:zona.participante"]],
                                         by="Effect", suffixes = c("","'"))
  df = get_anova_table(aov)
}

if (length(unique(pdat[["zona.participante"]])) >= 2) {
  pwcs <- list()
  pwcs[["zona.participante"]] <- emmeans_test(
    group_by(wdat, grupo), score.CI.pos ~ zona.participante,
    covariate = score.CI.pre, p.adjust.method = "bonferroni")
  pwcs[["grupo"]] <- emmeans_test(
    group_by(wdat, zona.participante), score.CI.pos ~ grupo,
    covariate = score.CI.pre, p.adjust.method = "bonferroni")
  
  pwc <- plyr::rbind.fill(pwcs[["grupo"]], pwcs[["zona.participante"]])
  pwc <- pwc[,c("grupo","zona.participante", colnames(pwc)[!colnames(pwc) %in% c("grupo","zona.participante")])]
}

if (length(unique(pdat[["zona.participante"]])) >= 2) {
  pwc.long <- emmeans_test(dplyr::group_by_at(wdat.long, c("grupo","zona.participante")),
                           score.CI ~ time,
                           p.adjust.method = "bonferroni")
  lpwc[["grupo:zona.participante"]] <- merge(plyr::rbind.fill(pwc, pwc.long),
                                         lpwc[["grupo:zona.participante"]],
                                         by=c("grupo","zona.participante","term",".y.","group1","group2"),
                                         suffixes = c("","'"))
}

if (length(unique(pdat[["zona.participante"]])) >= 2) {
  ds <- get.descriptives(wdat, "score.CI.pos", c("grupo","zona.participante"), covar = "score.CI.pre")
  ds <- merge(ds[ds$variable != "score.CI.pre",],
              ds[ds$variable == "score.CI.pre", !colnames(ds) %in% c("variable")],
              by = c("grupo","zona.participante"), all.x = T, suffixes = c("", ".score.CI.pre"))
  ds <- merge(get_emmeans(pwcs[["grupo"]]), ds,
              by = c("grupo","zona.participante"), suffixes = c(".emms", ""))
  ds <- ds[,c("grupo","zona.participante","n","mean.score.CI.pre","se.score.CI.pre",
              "mean","se","emmean","se.emms","conf.low","conf.high")]
  
  colnames(ds) <- c("grupo","zona.participante", "N", paste0(c("M","SE")," (pre)"),
                    paste0(c("M","SE"), " (unadj)"),
                    paste0(c("M", "SE"), " (adj)"), "conf.low", "conf.high")
  
  lemms[["grupo:zona.participante"]] <- merge(ds, lemms[["grupo:zona.participante"]],
                                          by=c("grupo","zona.participante"), suffixes = c("","'"))
}

if (length(unique(pdat[["zona.participante"]])) >= 2) {
  ggPlotAoC2(pwcs, "grupo", "zona.participante", aov, ylab = "Reading Irregular Correct Words",
             subtitle = which(aov$Effect == "grupo:zona.participante"), addParam = "errorbar") +
    ggplot2::scale_color_manual(values = color[["zona.participante"]]) +
    ggplot2::ylab("Reading Irregular Correct Words") +
    if (ymin.ci < ymax.ci) ggplot2::ylim(ymin.ci, ymax.ci)
}

if (length(unique(pdat[["zona.participante"]])) >= 2) {
  ggPlotAoC2(pwcs, "zona.participante", "grupo", aov, ylab = "Reading Irregular Correct Words",
               subtitle = which(aov$Effect == "grupo:zona.participante"), addParam = "errorbar") +
    ggplot2::scale_color_manual(values = color[["grupo"]]) +
    ggplot2::ylab("Reading Irregular Correct Words") +
    if (ymin.ci < ymax.ci) ggplot2::ylim(ymin.ci, ymax.ci)
}

if (length(unique(pdat[["zona.participante"]])) >= 2) {
  plots <- twoWayAncovaBoxPlots(
    wdat, "score.CI.pos", c("grupo","zona.participante"), aov, pwcs, covar = "score.CI.pre",
    theme = "classic", color = color[["grupo:zona.participante"]],
    subtitle = which(aov$Effect == "grupo:zona.participante"))
}

if (length(unique(pdat[["zona.participante"]])) >= 2) {
  plots[["grupo:zona.participante"]] + ggplot2::ylab("Reading Irregular Correct Words") +
  ggplot2::scale_x_discrete(labels=c('pre', 'pos')) +
  if (ymin < ymax) ggplot2::ylim(ymin, ymax)
}

if (length(unique(pdat[["zona.participante"]])) >= 2) {
  plots <- twoWayAncovaBoxPlots(
    wdat.long, "score.CI", c("grupo","zona.participante"), aov, pwc.long,
    pre.post = "time",
    theme = "classic", color = color$prepost)
}

if (length(unique(pdat[["zona.participante"]])) >= 2) 
  plots[["grupo:zona.participante"]] + ggplot2::ylab("Reading Irregular Correct Words") +
    if (ymin < ymax) ggplot2::ylim(ymin, ymax)

if (length(unique(pdat[["zona.participante"]])) >= 2) {
  ggscatter(wdat, x = "score.CI.pre", y = "score.CI.pos", size = 0.5,
            facet.by = c("grupo","zona.participante"), add = "reg.line")+
    stat_regline_equation(
      aes(label =  paste(..eq.label.., ..rr.label.., sep = "~~~~"))
    ) + ggplot2::ylab("Reading Irregular Correct Words") +
    if (ymin < ymax) ggplot2::ylim(ymin, ymax)
}

if (length(unique(pdat[["zona.participante"]])) >= 2) {
  ggscatter(wdat, x = "score.CI.pre", y = "score.CI.pos", size = 0.5,
            color = "grupo", facet.by = "zona.participante", add = "reg.line")+
    stat_regline_equation(
      aes(label =  paste(..eq.label.., ..rr.label.., sep = "~~~~"), color = grupo)
    ) +
    ggplot2::labs(subtitle = rstatix::get_test_label(aov, detailed = T, row = which(aov$Effect == "grupo:zona.participante"))) +
    ggplot2::scale_color_manual(values = color[["grupo"]]) +
    ggplot2::ylab("Reading Irregular Correct Words") +
    if (ymin < ymax) ggplot2::ylim(ymin, ymax)
}

if (length(unique(pdat[["zona.participante"]])) >= 2) {
  ggscatter(wdat, x = "score.CI.pre", y = "score.CI.pos", size = 0.5,
            color = "zona.participante", facet.by = "grupo", add = "reg.line")+
    stat_regline_equation(
      aes(label =  paste(..eq.label.., ..rr.label.., sep = "~~~~"), color = zona.participante)
    ) +
    ggplot2::labs(subtitle = rstatix::get_test_label(aov, detailed = T, row = which(aov$Effect == "grupo:zona.participante"))) +
    ggplot2::scale_color_manual(values = color[["zona.participante"]]) +
    ggplot2::ylab("Reading Irregular Correct Words") +
    if (ymin < ymax) ggplot2::ylim(ymin, ymax)
}

if (length(unique(pdat[["zona.participante"]])) >= 2) 
  res <- augment(lm(score.CI.pos ~ score.CI.pre + grupo*zona.participante, data = wdat))

if (length(unique(pdat[["zona.participante"]])) >= 2)
  shapiro_test(res$.resid)

if (length(unique(pdat[["zona.participante"]])) >= 2) 
  levene_test(res, .resid ~ grupo*zona.participante)

pdat = remove_group_data(dat[!is.na(dat[["grupo"]]) & !is.na(dat[["zona.escola"]]),],
                         "score.CI.pos", c("grupo","zona.escola"))
pdat = pdat[pdat[["zona.escola"]] %in% do.call(
  intersect, lapply(unique(pdat[["grupo"]]), FUN = function(x) {
    unique(pdat[["zona.escola"]][which(pdat[["grupo"]] == x)])
  })),]
pdat[["grupo"]] = factor(pdat[["grupo"]], level[["grupo"]])
pdat[["zona.escola"]] = factor(
  pdat[["zona.escola"]],
  level[["zona.escola"]][level[["zona.escola"]] %in% unique(pdat[["zona.escola"]])])

pdat.long <- rbind(pdat[,c("id","grupo","zona.escola")], pdat[,c("id","grupo","zona.escola")])
pdat.long[["time"]] <- c(rep("pre", nrow(pdat)), rep("pos", nrow(pdat)))
pdat.long[["time"]] <- factor(pdat.long[["time"]], c("pre","pos"))
pdat.long[["score.CI"]] <- c(pdat[["score.CI.pre"]], pdat[["score.CI.pos"]])

if (length(unique(pdat[["zona.escola"]])) >= 2) {
  aov = anova_test(pdat, score.CI.pos ~ score.CI.pre + grupo*zona.escola)
  laov[["grupo:zona.escola"]] <- get_anova_table(aov)
}

if (length(unique(pdat[["zona.escola"]])) >= 2) {
  pwcs <- list()
  pwcs[["zona.escola"]] <- emmeans_test(
    group_by(pdat, grupo), score.CI.pos ~ zona.escola,
    covariate = score.CI.pre, p.adjust.method = "bonferroni")
  pwcs[["grupo"]] <- emmeans_test(
    group_by(pdat, zona.escola), score.CI.pos ~ grupo,
    covariate = score.CI.pre, p.adjust.method = "bonferroni")
  
  pwc <- plyr::rbind.fill(pwcs[["grupo"]], pwcs[["zona.escola"]])
  pwc <- pwc[,c("grupo","zona.escola", colnames(pwc)[!colnames(pwc) %in% c("grupo","zona.escola")])]
}

if (length(unique(pdat[["zona.escola"]])) >= 2) {
  pwc.long <- emmeans_test(dplyr::group_by_at(pdat.long, c("grupo","zona.escola")),
                           score.CI ~ time,
                           p.adjust.method = "bonferroni")
  lpwc[["grupo:zona.escola"]] <- plyr::rbind.fill(pwc, pwc.long)
}

if (length(unique(pdat[["zona.escola"]])) >= 2) {
  ds <- get.descriptives(pdat, "score.CI.pos", c("grupo","zona.escola"), covar = "score.CI.pre")
  ds <- merge(ds[ds$variable != "score.CI.pre",],
              ds[ds$variable == "score.CI.pre", !colnames(ds) %in% c("variable")],
              by = c("grupo","zona.escola"), all.x = T, suffixes = c("", ".score.CI.pre"))
  ds <- merge(get_emmeans(pwcs[["grupo"]]), ds,
              by = c("grupo","zona.escola"), suffixes = c(".emms", ""))
  ds <- ds[,c("grupo","zona.escola","n","mean.score.CI.pre","se.score.CI.pre","mean","se",
              "emmean","se.emms","conf.low","conf.high")]
  
  colnames(ds) <- c("grupo","zona.escola", "N", paste0(c("M","SE")," (pre)"),
                    paste0(c("M","SE"), " (unadj)"),
                    paste0(c("M", "SE"), " (adj)"), "conf.low", "conf.high")
  
  lemms[["grupo:zona.escola"]] <- ds
}

if (length(unique(pdat[["zona.escola"]])) >= 2) {
  wdat = pdat 
  
  res = residuals(lm(score.CI.pos ~ score.CI.pre + grupo*zona.escola, data = wdat))
  non.normal = getNonNormal(res, wdat$id, plimit = 0.05)
  
  wdat = wdat[!wdat$id %in% non.normal,]
  
  wdat.long <- rbind(wdat[,c("id","grupo","zona.escola")], wdat[,c("id","grupo","zona.escola")])
  wdat.long[["time"]] <- c(rep("pre", nrow(wdat)), rep("pos", nrow(wdat)))
  wdat.long[["time"]] <- factor(wdat.long[["time"]], c("pre","pos"))
  wdat.long[["score.CI"]] <- c(wdat[["score.CI.pre"]], wdat[["score.CI.pos"]])
  
  
  ldat[["grupo:zona.escola"]] = wdat
  
  (non.normal)
}

if (length(unique(pdat[["zona.escola"]])) >= 2) {
  aov = anova_test(wdat, score.CI.pos ~ score.CI.pre + grupo*zona.escola)
  laov[["grupo:zona.escola"]] <- merge(get_anova_table(aov), laov[["grupo:zona.escola"]],
                                         by="Effect", suffixes = c("","'"))
  df = get_anova_table(aov)
}

if (length(unique(pdat[["zona.escola"]])) >= 2) {
  pwcs <- list()
  pwcs[["zona.escola"]] <- emmeans_test(
    group_by(wdat, grupo), score.CI.pos ~ zona.escola,
    covariate = score.CI.pre, p.adjust.method = "bonferroni")
  pwcs[["grupo"]] <- emmeans_test(
    group_by(wdat, zona.escola), score.CI.pos ~ grupo,
    covariate = score.CI.pre, p.adjust.method = "bonferroni")
  
  pwc <- plyr::rbind.fill(pwcs[["grupo"]], pwcs[["zona.escola"]])
  pwc <- pwc[,c("grupo","zona.escola", colnames(pwc)[!colnames(pwc) %in% c("grupo","zona.escola")])]
}

if (length(unique(pdat[["zona.escola"]])) >= 2) {
  pwc.long <- emmeans_test(dplyr::group_by_at(wdat.long, c("grupo","zona.escola")),
                           score.CI ~ time,
                           p.adjust.method = "bonferroni")
  lpwc[["grupo:zona.escola"]] <- merge(plyr::rbind.fill(pwc, pwc.long),
                                         lpwc[["grupo:zona.escola"]],
                                         by=c("grupo","zona.escola","term",".y.","group1","group2"),
                                         suffixes = c("","'"))
}

if (length(unique(pdat[["zona.escola"]])) >= 2) {
  ds <- get.descriptives(wdat, "score.CI.pos", c("grupo","zona.escola"), covar = "score.CI.pre")
  ds <- merge(ds[ds$variable != "score.CI.pre",],
              ds[ds$variable == "score.CI.pre", !colnames(ds) %in% c("variable")],
              by = c("grupo","zona.escola"), all.x = T, suffixes = c("", ".score.CI.pre"))
  ds <- merge(get_emmeans(pwcs[["grupo"]]), ds,
              by = c("grupo","zona.escola"), suffixes = c(".emms", ""))
  ds <- ds[,c("grupo","zona.escola","n","mean.score.CI.pre","se.score.CI.pre",
              "mean","se","emmean","se.emms","conf.low","conf.high")]
  
  colnames(ds) <- c("grupo","zona.escola", "N", paste0(c("M","SE")," (pre)"),
                    paste0(c("M","SE"), " (unadj)"),
                    paste0(c("M", "SE"), " (adj)"), "conf.low", "conf.high")
  
  lemms[["grupo:zona.escola"]] <- merge(ds, lemms[["grupo:zona.escola"]],
                                          by=c("grupo","zona.escola"), suffixes = c("","'"))
}

if (length(unique(pdat[["zona.escola"]])) >= 2) {
  ggPlotAoC2(pwcs, "grupo", "zona.escola", aov, ylab = "Reading Irregular Correct Words",
             subtitle = which(aov$Effect == "grupo:zona.escola"), addParam = "errorbar") +
    ggplot2::scale_color_manual(values = color[["zona.escola"]]) +
    ggplot2::ylab("Reading Irregular Correct Words") +
    if (ymin.ci < ymax.ci) ggplot2::ylim(ymin.ci, ymax.ci)
}

if (length(unique(pdat[["zona.escola"]])) >= 2) {
  ggPlotAoC2(pwcs, "zona.escola", "grupo", aov, ylab = "Reading Irregular Correct Words",
               subtitle = which(aov$Effect == "grupo:zona.escola"), addParam = "errorbar") +
    ggplot2::scale_color_manual(values = color[["grupo"]]) +
    ggplot2::ylab("Reading Irregular Correct Words") +
    if (ymin.ci < ymax.ci) ggplot2::ylim(ymin.ci, ymax.ci)
}

if (length(unique(pdat[["zona.escola"]])) >= 2) {
  plots <- twoWayAncovaBoxPlots(
    wdat, "score.CI.pos", c("grupo","zona.escola"), aov, pwcs, covar = "score.CI.pre",
    theme = "classic", color = color[["grupo:zona.escola"]],
    subtitle = which(aov$Effect == "grupo:zona.escola"))
}

if (length(unique(pdat[["zona.escola"]])) >= 2) {
  plots[["grupo:zona.escola"]] + ggplot2::ylab("Reading Irregular Correct Words") +
  ggplot2::scale_x_discrete(labels=c('pre', 'pos')) +
  if (ymin < ymax) ggplot2::ylim(ymin, ymax)
}

if (length(unique(pdat[["zona.escola"]])) >= 2) {
  plots <- twoWayAncovaBoxPlots(
    wdat.long, "score.CI", c("grupo","zona.escola"), aov, pwc.long,
    pre.post = "time",
    theme = "classic", color = color$prepost)
}

if (length(unique(pdat[["zona.escola"]])) >= 2) 
  plots[["grupo:zona.escola"]] + ggplot2::ylab("Reading Irregular Correct Words") +
    if (ymin < ymax) ggplot2::ylim(ymin, ymax)

if (length(unique(pdat[["zona.escola"]])) >= 2) {
  ggscatter(wdat, x = "score.CI.pre", y = "score.CI.pos", size = 0.5,
            facet.by = c("grupo","zona.escola"), add = "reg.line")+
    stat_regline_equation(
      aes(label =  paste(..eq.label.., ..rr.label.., sep = "~~~~"))
    ) + ggplot2::ylab("Reading Irregular Correct Words") +
    if (ymin < ymax) ggplot2::ylim(ymin, ymax)
}

if (length(unique(pdat[["zona.escola"]])) >= 2) {
  ggscatter(wdat, x = "score.CI.pre", y = "score.CI.pos", size = 0.5,
            color = "grupo", facet.by = "zona.escola", add = "reg.line")+
    stat_regline_equation(
      aes(label =  paste(..eq.label.., ..rr.label.., sep = "~~~~"), color = grupo)
    ) +
    ggplot2::labs(subtitle = rstatix::get_test_label(aov, detailed = T, row = which(aov$Effect == "grupo:zona.escola"))) +
    ggplot2::scale_color_manual(values = color[["grupo"]]) +
    ggplot2::ylab("Reading Irregular Correct Words") +
    if (ymin < ymax) ggplot2::ylim(ymin, ymax)
}

if (length(unique(pdat[["zona.escola"]])) >= 2) {
  ggscatter(wdat, x = "score.CI.pre", y = "score.CI.pos", size = 0.5,
            color = "zona.escola", facet.by = "grupo", add = "reg.line")+
    stat_regline_equation(
      aes(label =  paste(..eq.label.., ..rr.label.., sep = "~~~~"), color = zona.escola)
    ) +
    ggplot2::labs(subtitle = rstatix::get_test_label(aov, detailed = T, row = which(aov$Effect == "grupo:zona.escola"))) +
    ggplot2::scale_color_manual(values = color[["zona.escola"]]) +
    ggplot2::ylab("Reading Irregular Correct Words") +
    if (ymin < ymax) ggplot2::ylim(ymin, ymax)
}

if (length(unique(pdat[["zona.escola"]])) >= 2) 
  res <- augment(lm(score.CI.pos ~ score.CI.pre + grupo*zona.escola, data = wdat))

if (length(unique(pdat[["zona.escola"]])) >= 2)
  shapiro_test(res$.resid)

if (length(unique(pdat[["zona.escola"]])) >= 2) 
  levene_test(res, .resid ~ grupo*zona.escola)

pdat = remove_group_data(dat[!is.na(dat[["grupo"]]) & !is.na(dat[["score.CI.quintile"]]),],
                         "score.CI.pos", c("grupo","score.CI.quintile"))
pdat = pdat[pdat[["score.CI.quintile"]] %in% do.call(
  intersect, lapply(unique(pdat[["grupo"]]), FUN = function(x) {
    unique(pdat[["score.CI.quintile"]][which(pdat[["grupo"]] == x)])
  })),]
pdat[["grupo"]] = factor(pdat[["grupo"]], level[["grupo"]])
pdat[["score.CI.quintile"]] = factor(
  pdat[["score.CI.quintile"]],
  level[["score.CI.quintile"]][level[["score.CI.quintile"]] %in% unique(pdat[["score.CI.quintile"]])])

pdat.long <- rbind(pdat[,c("id","grupo","score.CI.quintile")], pdat[,c("id","grupo","score.CI.quintile")])
pdat.long[["time"]] <- c(rep("pre", nrow(pdat)), rep("pos", nrow(pdat)))
pdat.long[["time"]] <- factor(pdat.long[["time"]], c("pre","pos"))
pdat.long[["score.CI"]] <- c(pdat[["score.CI.pre"]], pdat[["score.CI.pos"]])

if (length(unique(pdat[["score.CI.quintile"]])) >= 2) {
  aov = anova_test(pdat, score.CI.pos ~ score.CI.pre + grupo*score.CI.quintile)
  laov[["grupo:score.CI.quintile"]] <- get_anova_table(aov)
}

if (length(unique(pdat[["score.CI.quintile"]])) >= 2) {
  pwcs <- list()
  pwcs[["score.CI.quintile"]] <- emmeans_test(
    group_by(pdat, grupo), score.CI.pos ~ score.CI.quintile,
    covariate = score.CI.pre, p.adjust.method = "bonferroni")
  pwcs[["grupo"]] <- emmeans_test(
    group_by(pdat, score.CI.quintile), score.CI.pos ~ grupo,
    covariate = score.CI.pre, p.adjust.method = "bonferroni")
  
  pwc <- plyr::rbind.fill(pwcs[["grupo"]], pwcs[["score.CI.quintile"]])
  pwc <- pwc[,c("grupo","score.CI.quintile", colnames(pwc)[!colnames(pwc) %in% c("grupo","score.CI.quintile")])]
}

if (length(unique(pdat[["score.CI.quintile"]])) >= 2) {
  pwc.long <- emmeans_test(dplyr::group_by_at(pdat.long, c("grupo","score.CI.quintile")),
                           score.CI ~ time,
                           p.adjust.method = "bonferroni")
  lpwc[["grupo:score.CI.quintile"]] <- plyr::rbind.fill(pwc, pwc.long)
}

if (length(unique(pdat[["score.CI.quintile"]])) >= 2) {
  ds <- get.descriptives(pdat, "score.CI.pos", c("grupo","score.CI.quintile"), covar = "score.CI.pre")
  ds <- merge(ds[ds$variable != "score.CI.pre",],
              ds[ds$variable == "score.CI.pre", !colnames(ds) %in% c("variable")],
              by = c("grupo","score.CI.quintile"), all.x = T, suffixes = c("", ".score.CI.pre"))
  ds <- merge(get_emmeans(pwcs[["grupo"]]), ds,
              by = c("grupo","score.CI.quintile"), suffixes = c(".emms", ""))
  ds <- ds[,c("grupo","score.CI.quintile","n","mean.score.CI.pre","se.score.CI.pre","mean","se",
              "emmean","se.emms","conf.low","conf.high")]
  
  colnames(ds) <- c("grupo","score.CI.quintile", "N", paste0(c("M","SE")," (pre)"),
                    paste0(c("M","SE"), " (unadj)"),
                    paste0(c("M", "SE"), " (adj)"), "conf.low", "conf.high")
  
  lemms[["grupo:score.CI.quintile"]] <- ds
}

if (length(unique(pdat[["score.CI.quintile"]])) >= 2) {
  wdat = pdat 
  
  res = residuals(lm(score.CI.pos ~ score.CI.pre + grupo*score.CI.quintile, data = wdat))
  non.normal = getNonNormal(res, wdat$id, plimit = 0.05)
  
  wdat = wdat[!wdat$id %in% non.normal,]
  
  wdat.long <- rbind(wdat[,c("id","grupo","score.CI.quintile")], wdat[,c("id","grupo","score.CI.quintile")])
  wdat.long[["time"]] <- c(rep("pre", nrow(wdat)), rep("pos", nrow(wdat)))
  wdat.long[["time"]] <- factor(wdat.long[["time"]], c("pre","pos"))
  wdat.long[["score.CI"]] <- c(wdat[["score.CI.pre"]], wdat[["score.CI.pos"]])
  
  
  ldat[["grupo:score.CI.quintile"]] = wdat
  
  (non.normal)
}

if (length(unique(pdat[["score.CI.quintile"]])) >= 2) {
  aov = anova_test(wdat, score.CI.pos ~ score.CI.pre + grupo*score.CI.quintile)
  laov[["grupo:score.CI.quintile"]] <- merge(get_anova_table(aov), laov[["grupo:score.CI.quintile"]],
                                         by="Effect", suffixes = c("","'"))
  df = get_anova_table(aov)
}

if (length(unique(pdat[["score.CI.quintile"]])) >= 2) {
  pwcs <- list()
  pwcs[["score.CI.quintile"]] <- emmeans_test(
    group_by(wdat, grupo), score.CI.pos ~ score.CI.quintile,
    covariate = score.CI.pre, p.adjust.method = "bonferroni")
  pwcs[["grupo"]] <- emmeans_test(
    group_by(wdat, score.CI.quintile), score.CI.pos ~ grupo,
    covariate = score.CI.pre, p.adjust.method = "bonferroni")
  
  pwc <- plyr::rbind.fill(pwcs[["grupo"]], pwcs[["score.CI.quintile"]])
  pwc <- pwc[,c("grupo","score.CI.quintile", colnames(pwc)[!colnames(pwc) %in% c("grupo","score.CI.quintile")])]
}

if (length(unique(pdat[["score.CI.quintile"]])) >= 2) {
  pwc.long <- emmeans_test(dplyr::group_by_at(wdat.long, c("grupo","score.CI.quintile")),
                           score.CI ~ time,
                           p.adjust.method = "bonferroni")
  lpwc[["grupo:score.CI.quintile"]] <- merge(plyr::rbind.fill(pwc, pwc.long),
                                         lpwc[["grupo:score.CI.quintile"]],
                                         by=c("grupo","score.CI.quintile","term",".y.","group1","group2"),
                                         suffixes = c("","'"))
}

if (length(unique(pdat[["score.CI.quintile"]])) >= 2) {
  ds <- get.descriptives(wdat, "score.CI.pos", c("grupo","score.CI.quintile"), covar = "score.CI.pre")
  ds <- merge(ds[ds$variable != "score.CI.pre",],
              ds[ds$variable == "score.CI.pre", !colnames(ds) %in% c("variable")],
              by = c("grupo","score.CI.quintile"), all.x = T, suffixes = c("", ".score.CI.pre"))
  ds <- merge(get_emmeans(pwcs[["grupo"]]), ds,
              by = c("grupo","score.CI.quintile"), suffixes = c(".emms", ""))
  ds <- ds[,c("grupo","score.CI.quintile","n","mean.score.CI.pre","se.score.CI.pre",
              "mean","se","emmean","se.emms","conf.low","conf.high")]
  
  colnames(ds) <- c("grupo","score.CI.quintile", "N", paste0(c("M","SE")," (pre)"),
                    paste0(c("M","SE"), " (unadj)"),
                    paste0(c("M", "SE"), " (adj)"), "conf.low", "conf.high")
  
  lemms[["grupo:score.CI.quintile"]] <- merge(ds, lemms[["grupo:score.CI.quintile"]],
                                          by=c("grupo","score.CI.quintile"), suffixes = c("","'"))
}